1. Field of the Invention
The present invention concerns in general terms a Multi-User Detection (MUD) method. More precisely, the present invention relates to an iterative method of eliminating interference between users (Multiple Access Interference or MAI). The present invention applies more particularly to mobile telephony in DS-CDMA (Direct Sequence-Code Division Multiple Access) mode, that is to say to mobile telephony using a code distribution access mode with direct sequence spectral spreading.
2. Discussion of the Background
In a DS-CDMA mobile telephony system, the separation of the different users is effected by multiplying each user symbol by a spreading sequence peculiar to it, also referred to for this reason as the user signature, the different signatures ideally being chosen so as to be orthogonal. The spreading sequence frequency (chip rate) being greater than the frequency of the symbols, the signal transmitted by each user is distributed (or spread) in the frequency space. On reception, the separation of the signal of a user is effected by means of a filtering adapted to the corresponding signature. This filtering is also referred to as “de-spreading”. The ratio between the band occupied by the spread signal and the band occupied by the information signal is referred to as the spread factor.
The signals employed must have good correlation properties, namely a very pronounced autocorrelation peak and very low intercorrelation values.
The first of these two characteristics enables the received sequence to be synchronised. It is very useful when the transmission channel of a user includes several propagation paths. This is because each path can then be isolated by virtue of a filtering adapted to the signature and to the delay of the path. Advantage can be taken of the propagation diversity within the channel to increase the signal to noise ratio on reception. For this purpose, a bank of adapted filters is used, separating the different paths, and the outputs are combined. The most widespread combination is MRC (Maximum Ratio Combining), which consists of multiplying the signal output from each adapted filter by the conjugate of the complex multiplying coefficient introduced by the channel on the path concerned. The resulting filtering operation is a filtering adapted to the equivalent filter of the channel. Because of its structure, the receiver thus formed is referred to as a rake receiver. Naturally, perfect separation of the path takes place only if the autocorrelation is a Dirac. In practice, however, the separation is not complete and leaves a multipath interference which is also referred to as self noise. FIG. 1 depicts schematically a DS-CDMA system with K users. The data of a user k are spread in frequency by the corresponding frequency in the module 100k before being transmitted over a channel 110k including P paths. On reception, for a given user k, the signals being propagated on the different paths p=1 . . . P of the channel are separated by adapted filters 120k,1 . . . 120k,P (only the battery of filters of the user k has been depicted) before being weighted by a set of complex coefficients Ck,p. The signals thus weighted are summed (140k) and the resulting sum at the output of the rake receiver is subsequently detected in order to provide an estimation of the data of the user k. In the case of a downlink (links from a base station to a mobile terminal) the channels 1 to K are identical whilst they are different in the uplink (links from mobile terminals to the base station). The first case can, from this point of view, be considered to be a particular case of the second.
The second characteristic set out above guarantees a low level of interference between two distinct users. Nevertheless, there too, in practice, the intercorrelation between two signatures is rarely zero. This is particularly the case in a so-called near-far effect situation, where a high-power signal received from a user interferes with the reception of a low-power signal coming from another user. Moreover, when the number of users is high, close to the spread factor, the sum of the interferences of the different users, low if taken in isolation, can have effects which interfere greatly with detection.
In order to combat multi-user interference, several methods have been proposed. A review of this will be found in the article by Simon Moshavi entitled “Multi-user detection for DS-CDMA communications” which appeared in IEEE Communications Magazine, October 1996, pages 124–136. Amongst existing multi-user techniques, the techniques of subtractive elimination (Subtractive Interference Cancellation) have good performance for reasonable complexity in use. The general idea of this is simple: from a first detection at the output of an adapted filter, the contributions to the interference suffered by the other users is reconstructed by respreading. This interference is next subtracted from the signal received in order to supply a cleaned signal at a subsequent detection step. According to the way in which the subtraction is effected, this is known as parallel elimination (PIC, standing for Parallel Interference Cancellation) and serial elimination (SIC, standing for Serial Interference Cancellation) of the interference.
The parallel elimination method is illustrated in FIG. 2: the signal received is filtered by a battery of adapted filters (2001, 2002, . . , 200K), each adapted filter relating to a given user. After detection (210k), the estimated symbols are respread (220k) spectrally by means of the signature of the user in question before being filtered by a filter modelling the transmission channel (230k). There is thus available at the output of (230k) an estimation of the contributory share of the signal received which can be attributed to the user k. From the signal received the sum of the contributory parts of the other users is subtracted (at (240k)) in order to obtain a cleaned signal Sk(1). This cleaned signal can directly be the subject of detection after despreading or the elimination process can be iterated. The detection being of better quality at each iteration, there is then obtained, as the successive iterations continue, signals Sk(i) which are better and better rid of the multi-user interference.
The serial elimination method is illustrated in FIG. 3: the signals received by the different users are first of all ordered in decreasing order of power, that is to say 1, . . . , K. The procedure then consists of successive eliminations of the contributory shares, commencing with the signal with the highest power. For this purpose, the SIC detector has a series of stages in cascade, each eliminating the interference due to a particular user. The first stage works on the antenna signal and each subsequent stage receives as an input the output of the previous stage. Each stage has an adapted filter (300k), a detector (310k), a module (320k) for respreading the symbols, a filter (330k) modelling the transmission channel k and a subtracter (340k) eliminating the contribution due to the user k. Each stage also supplies as an output of the detector (310k) a decision on the received symbol, Ŝk, and the interference elimination process ends at the Kth stage.
Another serial elimination method is detection by Zero-Forcing Decision-Feedback (ZF-DF). According to this method, illustrated in FIG. 4, the signal received is filtered and recombined by a battery of adapted filters (4001, . . . , 400K) before undergoing linear processing (405) consisting of a multiplication by the matrix (FT)−1 where F is the lower triangular matrix obtained by Cholesky decomposition of the correlation matrix R of the signatures of the different users (R=FT.F). The matrix processing has the effect of partially decorrelating the signals of the different users. The signals thus partially decorrelated are then subjected to a serial elimination, after having been classified in decreasing order of amplitude, that is to say A1, . . . , AK. The detector has a plurality of stages, each stage i comprising a detector (410i) whose output is multiplied by multipliers (415i,i+1), . . . ,(415i,K) in order to supply products Ai.Fk,i with i<k, where Fk,i is an element of the matrix F. At the input to each stage (k), there is subtracted (416i,k) the sum
      ∑          i      =      1              k      -      1        ⁢          ⁢            A      i        ·          F              k        ,        i              ·                  s        ^            i      where ŝi is the estimated symbol for the user i, that is to say the sum of the contributions of the previous users i<k. The decision (410k) relating to the symbol transmitted by the user k is taken from the signal thus cleaned. The estimated symbols ŝk of the different users are obtained by progressing from stage to stage.
The techniques set out above can be applied well to the simple situation where the transmission channel of a user has a single path. In this case, the filter modelling the channel can be limited to multiplication by a complex coefficient. When the channels are multi-path, the situation is on the other hand much more complex since it is necessary at the same time to eliminate multi-path interference and multi-user interference. An iterative detector with subtractive elimination of multi-user interference in the presence of multi-paths was proposed in an article by M. C. Reed et al. entitled “Iterative Multiuser detection using antenna arrays and FEC on multipath channels” published in the IEEE journal on Selected Areas in Communications, Vol. 17, No 12, December 1999, pages 2082–2089. Each iteration of the detection comprises an adapted filtering, a formation of channels and a combination of the rake type. The method proposed presupposes however that the coefficients of attenuation, the phase rotations and the directions of arrival of all the paths of all the users are determined. This determination can be effected for example by correlating the pilot symbols emitted by the different users in adapted filters. However, this determination is often imprecise, which results in an imperfect or even erroneous elimination of the multi-user interference.